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README.md
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---
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license: apache-2.0
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base_model: facebook/wav2vec2-large-xlsr-53
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tags:
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- generated_from_trainer
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metrics:
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- wer
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model-index:
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- name: wav2vec2-xlsr-53-ft-btb-cv-other-cy
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# wav2vec2-xlsr-53-ft-btb-cv-other-cy
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This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4934
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- Wer: 0.3776
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0003
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- train_batch_size: 8
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- eval_batch_size: 64
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 800
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- training_steps: 8000
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Wer |
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|:-------------:|:------:|:----:|:---------------:|:------:|
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| 5.1054 | 0.0755 | 500 | 2.8161 | 1.0 |
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| 1.4196 | 0.1509 | 1000 | 1.1687 | 0.7941 |
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| 1.0028 | 0.2264 | 1500 | 0.9890 | 0.6953 |
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| 0.8942 | 0.3019 | 2000 | 0.8935 | 0.6195 |
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| 0.8285 | 0.3774 | 2500 | 0.8221 | 0.6075 |
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| 0.763 | 0.4528 | 3000 | 0.7165 | 0.5307 |
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| 0.7203 | 0.5283 | 3500 | 0.6892 | 0.5054 |
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| 0.7051 | 0.6038 | 4000 | 0.6848 | 0.5070 |
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| 0.6568 | 0.6792 | 4500 | 0.6342 | 0.4926 |
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| 0.6315 | 0.7547 | 5000 | 0.5956 | 0.4494 |
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| 0.6171 | 0.8302 | 5500 | 0.5533 | 0.4305 |
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| 0.5717 | 0.9057 | 6000 | 0.5360 | 0.4212 |
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| 0.5699 | 0.9811 | 6500 | 0.5184 | 0.4040 |
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| 0.4905 | 1.0566 | 7000 | 0.5081 | 0.3967 |
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| 0.4706 | 1.1321 | 7500 | 0.4991 | 0.3825 |
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| 0.4614 | 1.2075 | 8000 | 0.4934 | 0.3776 |
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### Framework versions
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- Transformers 4.44.0
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- Pytorch 2.4.0+cu121
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- Datasets 2.21.0
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- Tokenizers 0.19.1
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